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Brick-and-mortar retailers should nix deep discounts to make most of jittery shopping season–Sharmila C. Chatterjee

December 19, 2016 – 10:01 am

MIT Sloan Senior Lecturer Sharmila Chatterjee

From The Conversation

Brick-and-mortar retailers have been on a bit of a roller coaster ride this holiday season as early expectations of strong consumer spending were weighed down by the uncertainty prompted by the election.

That’s on top of the usual jitters about the slow demise of Black Friday and more consumer cash gravitating to online retail.

That has made projections about this year’s holiday shopping season more of a guessing game than usual, but one aspect has now become clear: The rush by retailers to deeply discount merchandise will likely not prove to be beneficial to these retailers in the long term.

My research in “business to business” marketing suggests that instead of enacting ever-steeper price cuts that erode margins, both major retailers like Macy’s and small mom-and-pop stores would be much better off leveraging their physical presence as a source of strength rather than weakness by focusing on the personal touch that only they can provide.

From robust to jittery

Prior to the elections, analysts were predicting robust holiday shopping with spending expected to increase by 3.6 percent amid a strengthening economy.

Then Donald Trump was elected as U.S. president. Immediately, shoppers cut back spending, and some predicted a drop in purchases of big-ticket items due to the uncertainty. Pundits even said that “post-election trauma” meant consumers were too depressed, worried or stressed to shop.

One thought on “Brick-and-mortar retailers should nix deep discounts to make most of jittery shopping season–Sharmila C. Chatterjee”

Sharmila – I completely agree with your analysis. In fact this is a huge part of the SAS Institute Solutions (www.sas.com) in the areas of Regular and Promotional Price Optimization Solutions that we go to market with everyday. As an analytics person by trade we pitch the analytic optimization on markdowns as a example coupled with personalized interactions is how to get maximum return on inventory and leads to long term customer loyalty etc… Good read and independent validation. thanks…